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Optimal Policy Identification: Insights from the German Electricity Market

机译:最优政策识别:德国电力市场的见解

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The diffusion of renewable electricity generating technologies is widely considered as crucial for establishing a sustainable energy system in the future. However, the required transition is unlikely to be achieved by market forces alone. For this reason, many countries implement various policy instruments to support this process, also by re-distributing related costs among all electricity consumers. This paper presents a novel history-friendly agent-based study aiming to explore the efficiency of different mixes of policy instruments by means of a Differential Evolution algorithm. Special emphasis of the model is devoted to the possibility of small scale renewable electricity generation, but also to the storage of this electricity using small scale facilities being actively developed over the last decade. Both combined pose an important instrument for electricity consumers to achieve partial or full autarky from the electricity grid, particularly after accounting for decreasing costs and increasing efficiency of both due to continuous innovation. Among other things, we find that the historical policy mix of Germany introduced too strong and inflexible demand-side instruments (like feed-in tariff) too early, thereby creating strong path-dependency for future policy makers and reducing their ability to react to technological but also economic shocks without further increases of the budget.
机译:人们普遍认为,可再生能源发电技术的普及对未来建立可持续能源系统至关重要。但是,仅靠市场力量不可能实现所需的过渡。因此,许多国家还通过在所有用电者之间重新分配相关成本来实施各种政策工具来支持这一过程。本文提出了一种基于历史友好代理的新颖研究,旨在通过差分进化算法探索不同政策工具组合的效率。该模型的特别重点在于小规模可再生能源发电的可能性,同时也涉及在过去十年中积极开发的使用小型设施的电力存储。两者的结合构成了用电者从电网获得部分或全部自给自足的重要工具,尤其是在考虑到由于持续创新而降低了成本并提高了两者的效率之后。除其他外,我们发现德国的历史政策组合过早引入了过于强大和不灵活的需求方工具(例如上网电价),从而为未来的决策者建立了强大的路径依赖,并降低了他们对技术做出反应的能力。而且还会带来经济冲击,而无需进一步增加预算。

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